McCoy, M. B.Cevher, V.Dinh, Q. T.Asaei, A.Baldassarre, L.2016-02-082016-02-0820141053-5888http://hdl.handle.net/11693/26579Source separation, or demixing, is the process of extracting multiple components entangled within a signal. Contemporary signal processing presents a host of difficult source separation problems, from interference cancellation to background subtraction, blind deconvolution, and even dictionary learning. Despite the recent progress in each of these applications, advances in high-throughput sensor technology place demixing algorithms under pressure to accommodate extremely high-dimensional signals, separate an ever larger number of sources, and cope with more sophisticated signal and mixing models. These difficulties are exacerbated by the need for real-time action in automated decision-making systems. © 1991-2012 IEEE.EnglishConvolutionSignal processingBackground subtractionBlind deconvolutionDecision-making systemsDictionary learningInterference cancellationMultiple componentsSensor technologiesSeparation problemsAlgorithmsArticle10.1109/MSP.2013.2296605